|
|
|
Identification of unstable individuals in dynamic networks |
| Dongli Duan(段东立)1,†, Tao Chai(柴涛)1, Xixi Wu(武茜茜)1, Chengxing Wu(吴成星)1, Shubin Si(司书宾)2,3, and Genqing Bian(边根庆)1 |
1 School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710311, China;
2 School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, China;
3 Key Laboratory of Industrial Engineering and Intelligent Manufacturing(Ministry of Industry and Information Technology), Northwestern Polytechnical University, Xi'an 710072, China |
|
|
|
|
Abstract To identify the unstable individuals of networks is of great importance for information mining and security management. Exploring a broad range of steady-state dynamical processes including biochemical dynamics, epidemic processes, birth-death processes and regulatory dynamics, we propose a new index from the microscopic perspective to measure the stability of network nodes based on the local correlation matrix. The proposed index describes the stability of each node based on the activity change of the node after its neighbor is disturbed. Simulation and comparison results show our index can identify the most unstable nodes in the network with various dynamical behaviors, which would actually create a richer way and a novel insight of exploring the problem of network controlling and optimization.
|
Received: 23 December 2020
Revised: 03 February 2021
Accepted manuscript online: 24 February 2021
|
|
PACS:
|
05.10.-a
|
(Computational methods in statistical physics and nonlinear dynamics)
|
| |
64.60.aq
|
(Networks)
|
| |
89.75.-k
|
(Complex systems)
|
| |
89.75.Hc
|
(Networks and genealogical trees)
|
|
| Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 72071153 and 71771186), Key Laboratory of Science and Technology on Integrated Logistics Support (Grant Nos. 6142003190102), the Natural Science Foundation of Shaanxi Province, China (Grant Nos. 2020JM-486), and the China Postdoctoral Science Foundation (Grant No. 2017M613336). |
Corresponding Authors:
Dongli Duan
E-mail: mineduan@163.com
|
Cite this article:
Dongli Duan(段东立), Tao Chai(柴涛), Xixi Wu(武茜茜), Chengxing Wu(吴成星), Shubin Si(司书宾), and Genqing Bian(边根庆) Identification of unstable individuals in dynamic networks 2021 Chin. Phys. B 30 090501
|
[1] Jeong H, Tombor B, Albert R, Oltvai Z N and Barabasi A L 2000 Nature 407 651
[2] Crucitti P, Latora V and Marchiori M 2003 Phys. Rev. E 69 045104
[3] Weng W G, Ni S J, Shen S F and Yuan H Y 2007 Acta Phys. Sin. 56 1938 (in Chinese)
[4] Lu L Y, Chen D B, Ren X L, Zhang Q M, Zhang Y C and Zhou T 2016 Phys. Rep. 650 1
[5] Huang H, Ho D W and Lam J 2005 IEEE Trans. Circuits Systems Ⅱ 52 251
[6] Rakkiyappan R, Velmurugan G and Cao J 2014 Nonlinear Dyn. 78 2823
[7] Song Q, Zhao Z and Liu Y 2015 Neurocomputing 159 96
[8] Duan Z, Wang J, Chen G and Huang L 2008 Automatica 44 1028
[9] Liu X and Zou Y 2012 Int. J. Syst. Sci. 43 1950
[10] Liu X and Zou Y 2014 Multidimensional Systems and Signal Processing 25 531
[11] Li C H, Tsai C C and Yang S Y 2014 Commun. Nonlinear Sci. Numer. Simulat. 19 1042
[12] Wang Y, Cao J, Jin Z, Zhang H and Sun G Q 2013 Physica A 392 5824
[13] Zhang J and Sun J 2014 Physica A 394 24
[14] Lu Y L, Jiang G P and Song Y R 2013 Acta Phys. Sin. 62 537 (in Chinese)
[15] Danila B, Yu Y, Marsh JA and Bassler K E 2006 Phys. Rev. E 74 046106
[16] Yan G, Zhou T, Hu B, Fu Z Q and Wang B H 2006 Phys. Rev. E 73 046108
[17] Yang Y H, Liu Y G, Zhou M, Li F X and Sun C 2015 Safety Sci. 79 149
[18] Gao J, Barzel B and Barabasi A L 2016 Nature 530 307
[19] Barzel B and Barabasi A L 2013 Nat. Phys. 9 673
[20] Maslov S, Sneppen K and Ispolatov I 2007 New J. Phys. 9 273
[21] Yan K K, Walker D and Maslov S 2008 Phys. Rev. Lett. 101 268102
[22] Novozhilov A S, Karev V and Koonin E V 2006 Briefings in Bioinformatics 7 70
[23] Crawford F W and Suchard M A 2012 J. Math. Biol. 65 553
[24] Karlebach G and Shamir R 2008 Nat. Rev. Mol. Cell Biol. 9 770
[25] Foo M, Kim J and Bates D G 2018 IEEE/ACM Trans. Comput. Biol. Bioinform 19 1
[26] Pastor-Satorras R and Vespignani A 2018 Phys. Rev. Lett. 86 3200
[27] Qu B and Wang H J 2017 Physica A 472 13 |
| No Suggested Reading articles found! |
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
Altmetric
|
|
blogs
Facebook pages
Wikipedia page
Google+ users
|
Online attention
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
View more on Altmetrics
|
|
|
